Lebenswissenschaften und Ethik
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Background:
Adolescent substance use is a global and local (Hawaii) problem. Therefore, the study goal was to develop and investigate the effect of an adolescent substance use prevention intervention website in Hawaii.
Methods:
A website was developed including drug overviews, health effects, how to stay away, external prevention and treatment resources, and an evaluation. Three grade 11 classes completed a baseline (T1) survey based on website content and a follow-up (T2) assessment after a 15-minute website interaction. - Results: At T1, 63/72 and at T2, 62 students participated (16–17 years old; 92% female; 87.2% Filipino). The number correct increased from 48.0% (SD = 14.5) at T1 to 82.0% (SD = 15.3) at T2 (t(59) = 13.5, p < .001). Eleven of twelve topics improved (p < .5) which addressed mental disorder drug use, workplace meth-use in Hawaii, Americans in need of drug/alcohol treatment, stimulant drugs, side effects of drugs, drug related domestic/child abuse, short-term drug effects, Hawaii and national methuse, chemicals in drugs, how to stay away, and ways of treatment.
Conclusions:
Adolescents improved their substance use prevention understanding. This is promising considering the brief, inexpensive, potentially scalable intervention which can be implemented within high school curricula.
Risk factors for ulcerative colitis-associated colorectal cancer A retrospective cohort study
(2020)
Inflammatory bowel disease is associated with an increased risk of colorectal cancer. The study aims to identify the risk factors for ulcerative colitis-colorectal cancer and to perform a survival curve analysis of the outcome. This retrospective cohort study included 254 patients from March 2016 to October 2017. Age, age at diagnosis, follow-up time, smoking status, and family history of colorectal cancer were analyzed as risk factors for colorectal cancer. The mean patient age was 46.6 +/- 16.9 years; 5.5% of the patients were smokers and 49.6% had pancolitis. Six patients (2.36%) had colorectal cancer, which was associated with age at diagnosis (odds/hazard ratio 1.059 [95% confidence interval: 1.001-1.121];P = .04), family history of colorectal cancer (12.992 [1.611-104.7];P = .02), and follow-up time (0.665 [0.513-0.864];P = .002). Active smoking was the main identified risk factor, after both logistic (8.477 [1.350-53.232];P = .02) and Cox proportional-hazards (32.484 [2.465-428.1];P = .008) regression analysis. The risk of colorectal cancer was 3.17% at 10 years and 4.26% at 20 years of follow-up. Active smoking and family history were identified as risk factors for colorectal cancer. These findings should aid the early identification of patients who require vigorous surveillance, and prevent exposure to risk factors.
Background:
Chronic obstructive pulmonary disease (COPD) has a functional definition. However, differences in clinical characteristics and systemic manifestations make COPD a heterogeneous disease and some manifestations have been associated with different risks of acute exacerbations, hospitalizations, and death.
Objective:
Therefore, the objective of the study was to evaluate possible clinical clusters in COPD at two study centers in Brazil and identify the associated exacerbation and mortality rate during 1 year of follow-up.
Methods:
We included patients with COPD and all underwent an evaluation composed of the Charlson Index, body mass index (BMI), current pharmacological treatment, smoking history (packs-year), history of exacerbations/hospitalizations in the last year, spirometry, six-minute walking test (6MWT), quality of life questionnaires, dyspnea, and hospital anxiety and depression scale. Blood samples were also collected for measurements of C-reactive protein (CRP), blood gases, laboratory analysis, and blood count. For the construction of the clusters, 13 continuous variables of clinical importance were considered: hematocrit, CRP, triglycerides, low density lipoprotein, absolute number of peripheral eosinophils, age, pulse oximetry, BMI, forced expiratory volume in the first second, dyspnea, 6MWD, total score of the Saint George Respiratory Questionnaire and packs-year of smoking. We used the Ward and K-means methods and determined the best silhouette value to identify similarities of individuals within the cluster (cohesion) in relation to the other clusters (separation). The number of clusters was determined by the heterogeneity values of the cluster, which in this case was determined as four clusters.
Results:
We evaluated 301 COPD patients and identified four different groups of COPD patients. The first cluster (203 patients) was characterized by fewer symptoms and lower functional severity of the disease, the second cluster by higher values of peripheral eosinophils, the third cluster by more systemic inflammation and the fourth cluster by greater obstructive severity and worse gas exchange. Cluster 2 had an average of 959 3 peripheral eosinophils, cluster 3 had a higher prevalence of nutritional depletion (46.1%), and cluster 4 had a higher BODE index. Regarding the associated comorbidities, we found that only obstructive sleep apnea syndrome and pulmonary thromboembolism were more prevalent in cluster 4. Almost 50% of all patients presented an exacerbation during 1 year of follow-up. However, it was higher in cluster 4, with 65% of all patients having at least one exacerbation. The mortality rate was statistically higher in cluster 4, with 26.9%, vs 9.6% in cluster 1.
Conclusion:
We could identify four clinical different clusters in these COPD populations, that were related to different clinical manifestations, comorbidities, exacerbation, and mortality rate. We also identified a specific cluster with higher values of peripheral eosinophils.
Parkinson's disease (PD) is a neurodegenerative disease that affects millions of people worldwide, causing mental and mainly motor dysfunctions. The negative impact on the patient's daily routine has moved the science in search of new techniques that can reduce its negative effects and also identify the disease in individuals. One of the main motor characteristics of PD is the hand tremor faced by patients, which turns out to be a crucial information to be used towards a computer-aided diagnosis. In this context, we make use of handwriting dynamics data acquired from individuals when submitted to some tasks that measure abilities related to writing skills. This work proposes the application of recurrence plots to map the signals onto the image domain, which are further used to feed a Convolutional Neural Network for learning proper information that can help the automatic identification of PD. The proposed approach was assessed in a public dataset under several scenarios that comprise different combinations of deep-based architectures, image resolutions, and training set sizes. Experimental results showed significant accuracy improvement compared to our previous work with an average accuracy of over 87%. Moreover, it was observed an improvement in accuracy concerning the classification of patients (i.e., mean recognition rates above to 90%). The promising results showed the potential of the proposed approach towards the automatic identification of Parkinson's disease.
BACKGROUND:
Due to their corrugated profile, dragonfly wings have special aerodynamic characteristics during flying and gliding. OBJECTIVE: The aim of this study was to create a realistic 3D model of a dragonfly wing captured with a high-resolution micro-CT. To represent geometry changes in span and chord length and their aerodynamic effects, numerical investigations are carried out at different wing positions. METHODS:
The forewing of a Camacinia gigantea was captured using a micro-CT. After the wing was adapted an error-free 3D model resulted. The wing was cut every 5 mm and 2D numerical analyses were conducted in Fluent® 2020 R2 (ANSYS, Inc., Canonsburg, PA, USA). RESULTS: The highest lift coefficient, as well as the highest lift-to-drag ratio, resulted at 0 mm and an angle of attack (AOA) of 5∘. At AOAs of 10∘ or 15∘, the flow around the wing stalled and a Kármán vortex street behind the wing becomes
CONCLUSIONS:
The velocity is higher on the upper side of the wing compared to the lower side. The pressure acts vice versa. Due to the recirculation zones that are formed in valleys of the corrugation pattern the wing resembles the form of an airfoil.
English language skills are essential to professional communication in international engineering environments. Given the concomitant degree of specialization, university-level coursework in English for Specific Purposes is an essential component of engineering student preparation. This large-scale survey of university students of engineering in three European countries provides important insight into the most relevant language skills, with the goal of informing communicative, task-based curricula for Technical English courses.
Companies listed on the stock market must devote a great deal of attention to their market position. They must increase their competitive advantage in the undeniably key process of the issuance of stocks. As the issuance of preferred stocks has increased after the last crisis and in the current period of low interest rates in Europe, they are becoming more favoured investment instruments, we decided to analyse the real properties of preferred stocks in Europe in order to increase the efficiency of joint-stock companies. Using a dataset comprising all companies having both common and preferred stocks issued and traded on European markets between 2009- 2016, we determined the relationship of risk (measured by beta coefficients) and price volatility among common and preferred stocks and bonds in Europe. Our findings show beta coefficients of preferred stocks as systematically lower than beta coefficients of common stocks. Considering a difference of up to 10% as negligible, however, preferred stocks showed a similar or higher beta coefficient than corresponding common stocks of the same company in 53% of cases, whereas for 33% of cases, the difference is only ±10%. Coefficients of variation in prices showed a similar relationship, with only a negligible portion of preferred stocks bearing fixed (stable) dividends. This result implies that currently traded preferred stocks in Europe in fact do not possess such characteristics they are typically said to have, and in many cases they incur as comparable a risk as do common stocks. This essential information should help to increase the efficiency and competitiveness of joint-stock companies.
The early diagnosis of cancer in Barrett’s esophagus is crucial for improving the prognosis. However, identifying Barrett’s esophagus-related neoplasia (BERN) is challenging, even for experts [1]. Four-quadrant biopsies may improve the detection of neoplasia, but they can be associated with sampling errors. The application of artificial intelligence (AI) to the assessment of Barrett’s esophagus could improve the diagnosis of BERN, and this has been demonstrated in both preclinical and clinical studies [2] [3].
In this video demonstration, we show the accurate detection and delineation of BERN in two patients ([Video 1]). In part 1, the AI system detects a mucosal cancer about 20 mm in size and accurately delineates the lesion in both white-light and narrow-band imaging. In part 2, a small island of BERN with high-grade dysplasia is detected and delineated in white-light, narrow-band, and texture and color enhancement imaging. The video shows the results using a transparent overlay of the mucosal cancer in real time as well as a full segmentation preview. Additionally, the optical flow allows for the assessment of endoscope movement, something which is inversely related to the reliability of the AI prediction. We demonstrate that multimodal imaging can be applied to the AI-assisted detection and segmentation of even small focal lesions in real time.
Ergonomic workplaces lead to fewer work-related musculoskeletal disorders and thus fewer sick days. There are various guidelines to help avoid harmful situations. However, these recommendations are often rather crude and often neglect the complex interaction of biomechanical loading and psychological stress. This study investigates whether machine learning algorithms can be used to predict mechanical and stress-related muscle activity for a standardized motion. For this purpose, experimental data were collected for trunk movement with and without additional psychological stress. Two different algorithms (XGBoost and TensorFlow) were used to model the experimental data. XGBoost in particular predicted the results very well. By combining it with musculoskeletal models, the method shown here can be used for workplace analysis but also for the development of real-time feedback systems in real workplace environments.
This article presents results of the social-scientific evaluation of an established care model for people with dementia developed by the professionals as a result of acute problems in care in north-east Germany. In addition to the central elements of the model, the conditions of intersectoral and interprofessional cooperation as well as the qualification profile requirements of the professional groups involved are presented in detail. The results can give suggestions for the organization of integrated care for people with dementia in other countries. Further, the author would hereby like to highlight the gain from the scientific examination of solutions to problems in the field.